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Flux Stylizer V2.1 (Important Update)

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Description


ComfyUI Workflow: Transforming Photos into Studio Ghibli-Style Characters

Notes: Go to the change log for information about the new version.


I recommend Using the workflow with ComfyUI Desktop, as there are discrepancies between the Desktop and Portable versions, especially in the custom nodes.

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IMPORTANT: If you have already created custom styles, before downloading any updates, I recommend that you backUps the JSON strings.

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1. Introduction

Recently, OpenAI introduced an exciting new feature in ChatGPT: the ability to generate images that closely adhere to prompts and modify uploaded photos. As a result, many users have been experimenting with transforming real images into Studio Ghibli-style illustrations. However, ChatGPT’s free tier limits users to only three image modifications per day.

To overcome this limitation and provide unlimited image transformations, I created a workflow for ComfyUI that replicates the same effect, allowing for greater flexibility and continuous image generation.


Interfaccia Precedente

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2. Workflow Overview

The workflow follows these key steps:

  1. Image Input: The user provides a photo as input.
  2. Auto-Prompting with Florence2: The Florence2 model analyzes the input image and generates an automatic description.
  3. Prompt Refinement: The generated description is then modified to include key elements of Studio Ghibli’s art style and the trigger word required for the LoRA model.
  4. Image Generation with Flux Model: The core of this workflow is the Flux1.dev Hyper 8 steps GGUF Q8_0 model, which processes the refined prompt to generate a Studio Ghibli-style illustration.
  5. Preprocessing with ControlNet Depth: To ensure the output remains faithful to the input photo, ControlNet Depth is applied using the Flux_ControlNet-Union-Pro model as a preprocessor.
  6. Processing with Custom Advanced Sampler: The workflow utilizes the Custom Advanced Sampler for optimized image rendering.
  7. Postprocessing: To enhance the final output, the workflow applies: 15% monochromatic Gaussian noise for a vintage effect. 50% saturation boost to make colors more vivid.

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3. Models Used

Below is a list of the primary models used in this workflow, along with their corresponding links:

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4. Conclusion

This workflow allows users to transform real photos into Studio Ghibli-style illustrations while maintaining key facial and structural details. By integrating the models listed above, the system not only delivers high-quality results but also removes the generation restrictions found in the free version of ChatGPT.

This is the perfect solution for artists and AI enthusiasts who want to experiment freely and generate unlimited images.

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5. Change Log

09/04/2025 Important Update

IMPORTANT: If you have already created custom styles, before downloading any updates, I recommend that you backUps the JSON strings.


Flux Stylizer – v2.1

🔧 Major Enhancements

• JSON-based Custom Style Management

A new system has been implemented to manage custom styles through structured JSON strings. This includes:

  • A simplified syntax, easier to write and maintain.
  • An internal parser that auto-formats entries to ensure valid JSON.
  • A predefined structure that improves both readability and integration with the workflow UI.

• Persistent Style Storage via File System

Custom style definitions are now saved in external files, allowing persistence across sessions. Key points:

  • A new subfolder models/JSON/ must be manually created to store the JSON configuration file.
  • On first startup, the workflow will auto-generate a data file if none exists.
  • The workflow now loads styles from the file, not from the in-workflow JSON node, although the node is still present as a safety fallback.

⚙️ Workflow Behavior Options

New "Mode" Node for Customization

The workflow now includes a centralized "Mode" control node with several toggles:

  • AutoPrompt: Automatically generates prompts from input images using the Florence2 template. Can be disabled to allow manual prompt input.
  • Creative Mode: Prioritizes stylistic freedom over pose accuracy. When disabled, a depth map is used to closely match the input image’s structure.
  • Ultimate SD Upscale: Enables 2x upscaling via the "Ultimate SD Upscale" node. Increases quality, but also processing time.
  • Save Image / Save Compare: Control saving of generated images and comparison images. Self-explanatory toggle switches.

📝 Improved Documentation

  • The manual now includes a complete tutorial on how to add new styles using the new JSON format.
  • Examples and detailed breakdowns are provided to help users write valid custom style entries.
  • Instructions cover advanced behavior such as handling apostrophes in strings using escape characters (\').

🐛 Bug Fixes

• LoRA Path Resolution

Fixed an issue where LoRAs placed in the root of the models/loras/ directory were not recognized by the LoRA Switcher node.

→ LoRA models now work whether they are in subfolders or directly in the root path.


07/04/2025 Bug fix

Bug Fix Update – LoRA Path Handling

I've just uploaded a small update to the workflow to fix an issue that occurred when LoRA models were placed directly in the root of the models/loras/ folder. Previously, the LoRA Switcher node couldn't correctly detect styles unless they were inside a subfolder. This behavior has now been corrected—LoRAs placed directly in the root directory should work as expected.

Thanks again to everyone who provided feedback and helped identify the problem. Let me know if you encounter any further issues!


03/04/2025 Version 2.0

In this workflow update, I’ve worked on making it more customizable and configurable for the end user, allowing the addition of new styles easily and quickly. Now, the workflow is no longer limited to creating the Studio Ghibli style, it can generate any style you want.

As a result, I’ve also updated the name: it could no longer remain the original one, so it is now called Flux Stylizer V2.0.


To enable this flexibility, I structured the data in JSON format, using nodes that read and extract values associated with specific keys. Additionally, I’ve integrated a manual directly into the workflow, accessible via a "NOTE" node, which explains in detail how to:

  • Add new styles
  • Insert LoRA models and their trigger words
  • Use specific strings to reinforce styles in prompts

If you have any questions about adding new styles, feel free to ask in the comments, and I’ll reply as soon as possible.

Another key update is the ability to write a custom prompt instead of using Florence2’s automatic one. I’ve also introduced a method based on IPAdapter to preserve image consistency and color accuracy. Moreover, I’ve added an option to activate a creative mode. All these details can be found in another "NOTE" node, located on the right side of the workflow interface.

I hope this update is well received, as it makes the workflow more versatile, allowing you to replicate any style you desire.

Below are 3 trials with different styles, autoprompt ON and Creative Mode ON

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Primitive Nodes (108)

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Anything Everywhere3 (1)

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Compare-🔬 (1)

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easy isFileExist (1)

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  • - LayerUtility: PurgeVRAM (2)

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  • - > Scale Image to Side (1)

  • - > Int to Text (1)

  • - GetTextFromJson (5)

  • - Big Int Switch [Dream] (1)

  • - Big Text Switch [Dream] (1)

  • - GetImageSizeAndCount (1)

  • - String Replace (mtb) (1)

  • - Replace Text _O (6)

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3DMM_V12.safetensors

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Flux.1\Alex_Ross_StyleF1.safetensors